Unleash the AI Revolution: From Zero to Deployment with LLMs
Discover the future of AI and MLOps on AWS with 5+ hours of intensive instruction. Transition from theory to practice and elevate your skills with our comprehensive guide. Ready to deep-dive into the world of Meta AI's LLaMA 2 Large Language Model (LLM) on Amazon SageMaker? Let's get started.
Let's Dive into AI →
"AI and machine learning specialist is projected to be the fastest-growing job from 2023 to 2027"
- World Economic Forum's Future of Jobs Report 2023 (Business Insider)
Dive into the Exciting World of AI
We keep reading headlines saying that AI is taking over the world, and maybe you're thinking...
"AI is TOO hard to learn"
or
"I'm TOO late to this industry"
or
"I don't have ENOUGH experience"
Trust me, I've been there.
This is why you need to start right now.
I thought the same thing when I started diving down the tech rabbit hole. Everything is always hardest the first time you learn it. Walking for the first time, talking for the first time, getting your first job. It's all difficult.
But something you can do to keep up with the rapidly changing world of tech is take 10 or 20 steps every day towards your goal and rapidly change your future trajectory. I'm in your corner. That's how we'll win together!
Course overview
In this bundle, you will be diving into what I think is the most exciting area of Artificial Intelligence and Machine Learning. Here are the parts of the course and what you'll be learning to get an overview:
Dive into the Exciting World of AI
PART 1: Launch Your Own LLM
🎥 Fast-Track Your LLM Deployment: Learn to unleash the LLaMA 2 on Amazon SageMaker coupled with Hugging Face Deep Learning Containers (DLCs) in a short span of under 2 hours.
📚 Topics:
- Getting hands-on with Meta AI's LLaMA models
- Learning how Large Language Models work
- Seamless setup of Amazon SageMaker and Hugging Face DLCs
- Crafting robust SageMaker endpoints
PART 2: Transform Your AI Model into a Tangible Product
🎥 Versatile Product Building: Master the art of utilizing your deployed model to its fullest potential by converting it into a real-world functional product.
📚 Topics:
- Seamless integration with API Gateway for model access
- Harnessing AWS Lambda for serverless functionalities
- Python scripting mastery for nuanced model manipulation
- Dive into Next.js App development for a comprehensive product outlook
PART 3: Learn How to Clean Up SageMaker & Cut Costs
🎥 Optimize Your Cloud Spend With Endpoint Management: AI/ML can get expensive, so we need to make sure that we manage our environment correctly. Learn how to manage the most expensive services that you will deploy in your MLOps pipelines.
📚 Topics:
- Navigating the SageMaker Console Dashboard with deployed resources
- Learn how to decommission your AI/ML endpoint
- Discover how to clean up your SageMaker environment with Python and with the AWS Management Console
Ready to learn cutting edge AI/ML skills?
Get started here:
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What are you waiting for? Dive in here:
Leap into the tech vortex with the Tech Stack Playbook®:
